The latest AI news we announced in December
Favorite Here are Google’s latest AI updates from December including Gemini 2.0, GenCast, and Willow. View Original Source (blog.google/technology/ai/) Here.
Design multi-agent orchestration with reasoning using Amazon Bedrock and open source frameworks
Favorite As generative AI capabilities evolve, successful business adoptions hinge on the development of robust problem-solving capabilities. At the forefront of this transformation are agentic systems, which harness the power of foundation models (FMs) to tackle complex, real-world challenges. By seamlessly integrating multiple agents, these innovative solutions enable autonomous collaboration,
Read More
Shared by AWS Machine Learning December 20, 2024
An introduction to preparing your own dataset for LLM training
Favorite Large language models (LLMs) have demonstrated remarkable capabilities in a wide range of linguistic tasks. However, the performance of these models is heavily influenced by the data used during the training process. In this blog post, we provide an introduction to preparing your own dataset for LLM training. Whether your
Read More Shared by AWS Machine Learning December 20, 2024
Add a generative AI experience to your website or web application with Amazon Q embedded
Favorite Generative AI offers many benefits for both you, as a software provider, and your end-users. AI assistants can help users generate insights, get help, and find information that may be hard to surface using traditional means. In addition, they can help your employees reduce repetitive tasks and focus on
Read More Shared by AWS Machine Learning December 20, 2024
2024 end-of-year review: policy and standards
Favorite As 2024 draws to a close, the Open Source Initiative (OSI) reflects on an eventful year marked by significant achievements in advocating for Open Source principles in policy and standards development worldwide. Below, we highlight key milestones, initiatives and ongoing work from the year. Global engagements Columbia Convening on
Read More
Shared by voicesofopensource December 19, 2024
Using natural language in Amazon Q Business: From searching and creating ServiceNow incidents and knowledge articles to generating insights
Favorite Many enterprise customers across various industries are looking to adopt Generative AI to drive innovation, user productivity, and enhance customer experience. Generative AI–powered assistants such as Amazon Q Business can be configured to answer questions, provide summaries, generate content, and securely complete tasks based on data and information in
Read More Shared by AWS Machine Learning December 19, 2024
How Fastweb fine-tuned the Mistral model using Amazon SageMaker HyperPod as a first step to build an Italian large language model
Favorite This post is co-written with Marta Cavalleri and Giovanni Germani from Fastweb, and Claudia Sacco and Andrea Policarpi from BIP xTech. AI’s transformative impact extends throughout the modern business landscape, with telecommunications emerging as a key area of innovation. Fastweb, one of Italy’s leading telecommunications operators, recognized the immense
Read More Shared by AWS Machine Learning December 19, 2024
5 ways Open Health Stack is helping developers address healthcare gaps
Favorite Open Health Stack, a set of open-source tools from Google, allows developers to create digital health solutions for low-resource settings around the world. View Original Source (blog.google/technology/ai/) Here.
How TUI uses Amazon Bedrock to scale content creation and enhance hotel descriptions in under 10 seconds
Favorite TUI Group is one of the world’s leading global tourism services, providing 21 million customers with an unmatched holiday experience in 180 regions. TUI Group covers the end-to-end tourism chain with over 400 owned hotels, 16 cruise ships, 1,200 travel agencies, and 5 airlines covering all major holiday destinations
Read More Shared by AWS Machine Learning December 18, 2024
Simplify multimodal generative AI with Amazon Bedrock Data Automation
Favorite Developers face significant challenges when using foundation models (FMs) to extract data from unstructured assets. This data extraction process requires carefully identifying models that meet the developer’s specific accuracy, cost, and feature requirements. Additionally, developers must invest considerable time optimizing price performance through fine-tuning and extensive prompt engineering. Managing
Read More Shared by AWS Machine Learning December 18, 2024